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Intelligent Integrated Dynamic Surveillance Tool Improves Field Management Practices

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This paper describes solutions developed using a dynamic surveillance tool to automate several workflow processes of the reservoir management, production engineering, and R&D Center at Saudi Aramco. The objective is to provide improved efficiency in field management practices, while enhancing collaboration between reservoir and production engineers; ultimately resulting in improved decision-making process. The solutions provided include a combination of smart tools and automated workflows designed to improve reservoir management and surveillance processes. A candidate recognition system was developed to identify and flag problem wells that require immediate remediation. As new production and injection data become available, the system that is linked to the corporate database can automatically display these data for fast and rigorous validation. In addition, a formation damage indicator function is also calculated using field data and mapped to spot production problem areas and identify damaged wells. A daily surveillance tool, which compares the performance of individual wells to the average performance of a group of wells, is also provided to allow the reservoir and production engineers to easily identify under-performing wells, promptly intervene, and recommend best completion practices. Benefits include efficient well management and cost avoidance resulting from early intervention and remediation, while avoiding full-scale problem resolution. Another dynamic surveillance tool was designed and views were developed to provide online access to the hydrocarbon phase behavior and petrophysical data for the R&D scientists and reservoir engineers. The tool allows integration of the hydrocarbon phase-behavior data and comparison of petrophysical data with historical production/injection data and production well logs, resulting in enhanced analysis, production optimization and data validation. Additional benefits of the smart tools and automated workflow processes include considerable timesavings, with pertinent data being automatically updated, validated and used in the analysis, leading to improved efficiency in field management practices. Introduction It is generally accepted that most of the reservoir and production engineers' time is spent in searching, collecting, checking, and integrating reservoir and production data. Less time is spent by engineers on analysis and interpretation. Each engineer uses different tools in gathering this data, resulting in less collaboration and possible repetition of tasks. One of the main objectives of the integrated dynamic surveillance tool is to reduce the spent time on data gathering; letting engineers focus on data analysis and interpretation rather than data collection, leading to more efficient use of their time and increased collaboration between reservoir and production engineers. In this paper, four sets of tools are provided to automate reservoir management and surveillance, monitor production data, provide an integrated online access to hydrocarbon phase behavior and petrophysical data, and to manage well test knowledge. Reservoir Management and Surveillance Tools One of the reservoir engineer's main tasks is to manage the reservoir as efficiently as possible in order to prolong the life of the reservoir, while maximizing hydrocarbon recovery. Our aim is to provide the engineer with the necessary software tools to automate their workflow processes, while integrating computing processes and data, based on multidisciplinary asset team approach. Some of the tools developed to aid in this task include a remedial well analysis tool, a water management tool, a heterogeneity index tool, a formation damage indicator, and an integrated reservoir analysis tool.
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SPE 99555
Intelligent Integrated Dynamic Surveillance Tool Improves Field Management Practices
Saud M. Al-Fattah, SPE, M. M. Dallag, R. A. Abdulmohsin, W. A. Al-Harbi, and M. B. Issaka, SPE, Saudi Aramco
Copyright 2006, Society of Petroleum Engineers
This paper was prepared for presentation at the 2006 SPE Intelligent Energy Conference and
Exhibition held in Amsterdam, The Netherlands, 11–13 April 2006.
This paper was selected for presentation by an SPE Program Committee following review of
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presented, have not been reviewed by the Society of Petroleum Engineers and are subject to
correction by the author(s). The material, as presented, does not necessarily reflect any
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Abstract
This paper describes solutions developed using a dynamic
surveillance tool to automate several workflow processes of
the reservoir management, production engineering, and R&D
Center at Saudi Aramco. The objective is to provide improved
efficiency in field management practices, while enhancing
collaboration between reservoir and production engineers;
ultimately resulting in improved decision-making processes.
The solutions provided include a combination of smart
tools and automated workflows designed to improve reservoir
management and surveillance processes. A candidate
recognition system was developed to identify and flag
problem wells that require immediate remediation. As new
production and injection data become available, the system
that is linked to the corporate database can automatically
display this data for fast and rigorous validation. In addition, a
formation damage indicator function is also calculated using
field data and mapped to spot production problem areas and
identify damaged wells. A daily surveillance tool, which
compares the performance of individual wells to the average
performance of a group of wells, is also provided to allow the
reservoir and production engineers to easily identify under-
performing wells, promptly intervene, and recommend best
completion practices. Benefits include efficient well
management and cost avoidance resulting from early
intervention and remediation, while avoiding full-scale
problem resolution.
Another dynamic surveillance tool was designed and views
were developed to provide online access to the hydrocarbon
phase behavior and petrophysical data for the R&D scientists
and reservoir engineers. The tool allows integration of the
hydrocarbon phase-behavior data and comparison of
petrophysical data with historical production/injection data
and production well logs, resulting in enhanced analysis,
production optimization and data validation. Additional
benefits of the smart tools and automated workflow processes
include considerable timesavings, with pertinent data being
automatically updated, validated and used in the analysis,
leading to improved efficiency in field management practices.
Introduction
It is generally accepted that most of the reservoir and
production engineers’ time is spent in searching, collecting,
checking, and integrating reservoir and production data. Less
time is spent by engineers on analysis and interpretation. Each
engineer uses different tools in gathering this data, resulting in
less collaboration and possible repetition of tasks. One of the
main objectives of the integrated dynamic surveillance tool is
to reduce the spent time on data gathering; letting engineers
focus on data analysis and interpretation rather than data
collection, leading to more efficient use of their time and
increased collaboration between reservoir and production
engineers. In this paper, four sets of tools are provided to
automate reservoir management and surveillance, monitor
production data, provide an integrated online access to
hydrocarbon phase behavior and petrophysical data, and to
manage well test knowledge.
Reservoir Management and Surveillance Tools
One of the reservoir engineer’s main tasks is to manage the
reservoir as efficiently as possible in order to prolong the life
of the reservoir, while maximizing hydrocarbon recovery. Our
aim is to provide the engineer with the necessary software
tools to automate their workflow processes, while integrating
computing processes and data, based on multidisciplinary
asset team approach. Some of the tools developed to aid in this
task include a remedial well analysis tool, a water
management tool, a heterogeneity index tool, a formation
damage indicator, and an integrated reservoir analysis tool.
Remedial Well Analysis Tool
A candidate recognition system was developed to identify and
flag problem wells that require immediate remediation. The
system consists of various analysis tools that allow
anticipating the onset of problems by leveraging existing
knowledge from nearby wells. Figure 1 shows a typical plot
of the remedial well analysis tool. It summarizes the
production performance of a well by tracking the oil and water
production rates. These rates are then extended to forecast
their future production using decline curve analysis. This
allows early detection of mechanical and other problems such
as high water cut, low productivity or injectivity. The tool also
has the ability to identify the occurrence of production logs,
workover and stimulation jobs. The occurrence of well
pressure build-up and fall-off tests can also be identified. Also
2 SPE 99555
included in the tool is the identification and explanation of
well events that took place. This includes workover and/or
stimulation jobs. Using this tool, the engineer can anticipate
the onset of problems by leveraging existing knowledge from
nearby wells. Benefits include cost avoidance resulting from
early intervention and remediation, while avoiding full-scale
problem resolution.
Water Management Tool
The integrated dynamic surveillance tool was also used to
implement water management strategies for identifying and
controlling high water producing wells and cyclic production
wells. Based on reservoir management specified criteria, this
application allows the reservoir engineer to rapidly screen the
entire field for high water producing wells and recommend the
best reservoir management practices for the candidate wells.
These wells can be recommended for water shut-off,
stimulation, rate restriction, and sidetracking. Figures 2 and 3
show a field example of a carbonate reservoir with wells
producing up to 22,000 bbl/d, 90% water cut, and oil pay
thickness ranging from 20 ft. to 160 ft. Wells are screened by
selected criteria based on reservoir performance. For example,
in Figs. 2 and 3, the wells were screened based on arbitrary
cut-offs of 50% water cut, 40 ft. oil pay thickness, and 5000
bbl/d oil rate. Wells with low water cut (<50%) and high net
pay thickness (>40 ft) are considered as excellent wells. On
the other hand, wells with high water cut (>50%) and high net
pay thickness are prime candidates for workover, stimulation,
and/or rate restriction.
Another water diagnostic technique1 was also
implemented to help identifying and controlling high water
producing wells. Figure 4 illustrates the use of this technique
that employs both water/oil ratio and water cut derivatives
with respect to producing time. Using this tool, the source of
excessive water production can be identified due to either
channeling, water coning, or high oil production, and best
reservoir management practice is recommended.
Heterogeneity Index
This tool provides a convenient means of comparing the
performance of individual wells to the average of a group of
wells. This daily surveillance tool allows the engineer to
rapidly identify over- and under-performing wells, and
recommend the best completion practices. The heterogeneity
index2,3 (HI) is defined as
1
=
wellsavg
well
Value
Value
HI ……………………………. (1)
One is subtracted from the ratio to normalize the
heterogeneity index to zero, i.e., the average of all the wells is
equal to zero. Wells performing above the average will have a
value of HI that is larger than zero. HI values below zero
indicate wells performing below the average. HI can be
calculated for any dynamic variable such as production rate
and water cut. HI calculated from production rates could be
very noisy and hard to analyze. Therefore, a cumulative HI is
introduced to smooth the production rate HI as follows:
=HIHICum ……………………………….. ... (2)
Figure 5 shows a scatter plot of the heterogeneity index
based on cumulative production rates and another scatter plot
showing the well locations. Wells falling in the lower-right
quadrant of the HI plot are strong performers, with higher than
average oil rates and lower than average water rates. Analysis
of cumulative HI with time includes not only the relative
position of the point but also the slope of the curve (trend
analysis). This heterogeneity index should not be confused
with the formation heterogeneity.
Formation Damage Indicator
The use of the formation damage indicator is to spot
production problem areas and identify damaged wells.
Calculation of the skin factor can easily indicate which wells
have formation damage problems using a steady state flow
equation.
+
Δ
=
s
r
r
B
pkh
q
w
e
oo ln
007078.0
μ
………………………………… (3)
However, some of the fields have limited pressure data.
Therefore, by rearranging the equation, we can correlate it
with the formation damage index3 (FDI).
+
Δ
==
s
r
r
B
p
kh
q
FDI
w
e
oo ln
007078.0
μ
………………………. (4)
The numerator is the production rate that represents the
capacity of a well to produce. The denominator is the product
of the permeability and the pay zone thickness. It represents
the storage capacity of the formation to deliver. If a well has
formation damage problems, then it will produce at a low rate
even though the formation has a high storage capacity to
deliver. Hence, the formation damage index will be a low
value. Figure 6 shows a grid map of the formation damage
index. Areas colored in dark red have a high formation
damage index, while areas in yellow have low damage. The
green-colored areas have moderate damage. With this tool the
engineer can quickly and easily identify and quantify all
damaged wells of a given field with much less time and
convenience than the traditional way.
Integrated Reservoir Analysis Tool
An integrated reservoir analysis tool was also developed,
detailing the workflow process carried out by a reservoir
engineer in analyzing reservoir performance and production
data. Figure 7 shows a field example of several well analyses
tools integrated into single dynamic surveillance application.
The integrated reservoir analysis tool allows engineers and
geoscientists to view, report, map, and analyze reservoir
performance and production data with ease and convenience.
Among other applications, the integrated analysis tool was
used to analyse reservoir performance through historical
production/injection data, production forecast using decline
curve analysis, single and multiple production well logs,
stratigraphic cross sections, well deviations, and wellbore
SPE 99555 3
schematics of any particular well or a group of wells in a
given field.
The integrated tool can also be used as a useful means of
characterizing the field in a macroscopic scale. The base map
of a field includes the original oil-water contact, gas-oil
contact, faults, fractures, and geological structures of the field.
The integrated reservoir analysis tool was also used in the
waterflood management by monitoring the floodfront
movement, and studying the water encroachment through
mapping the fluid contact movement with time and the
geochemical water analysis. Additional analyses to study the
water encroachment in oil producing wells at the crest of the
field include mapping and displaying of flowing wellhead
pressure, flowing wellhead temperature, cumulative water cut,
and cumulative oil cut.
The Hall plot technique4,5 was also implemented and
integrated in the dynamic surveillance tool for analyzing
injection wells with the assumption of a series of steady-state
injection conditions. A Hall plot, as shown in Figure 8, is a
plot that displays the cumulative water injection on the x-axis
and the Hall coefficient on the y-axis. The Hall coefficient is a
running sum of the injection pressures for a water injection
well. This technique was deployed and used in waterflood
studies resulting in better reservoir understanding, and
improved efficiency in monitoring and control of injection
performance, and management of waterflood project.
Production Data Monitoring Tools
Automated real-time or near real-time production data plays
an important role for monitoring day-to-day reservoir
performance and field operational activities. Through the
integrated dynamic surveillance tool, we developed views to
provide automated real-time access to the daily gas production
data, and to the central production-data-acquisition systems of
oil and gas fields at Saudi Aramco. A brief description of
these tools follows.
Daily Gas Production Data
Having access to gas production data on a daily basis is
critical for monitoring the performance of gas wells. We
automated the updating of the daily gas production data,
making it available online to the gas reservoir management
and gas production engineering through an integrated dynamic
surveillance tool. The engineers now have access to all
historical gas production data up to present for all gas wells,
which is crucial to the efficient management of gas fields. It
provides reservoir and production engineers an online access
to gas production data on a daily basis, enabling close
monitoring of production performance of gas wells, predicting
instantaneous gas production rates, detecting production
problems, and tracking the compliance of the well production
to the reservoir management guidelines. Figure 9 shows a
comparison of the past and current workflow processes of the
daily gas production data.
Real Time Data Coupling to PI and SCADA Systems
Among the solutions provided in this tool, include a system
for real time data retrieval, visualization, and analysis of
reservoir production performance. This is achieved by linking
the integrated dynamic surveillance tool with Plant
Information (PI) and Supervisory Control and Data
Acquisition (SCADA) systems. Figure 10 shows the
integrated workflow process of real-time data coupling to the
PI and SCADA systems. With this tool, data such as daily
fluid rates, condensate rates, wellhead pressures and
temperatures can be provided in real-time at the engineer’s
desktop. These real-time data are critical for the day-to-day
monitoring of wells performance, troubleshooting, and
optimization, leading to improved efficiency of field
management practices.
Rock and Fluid Data Analysis Systems
Hydrocarbon phase-behavior data and petrophysical core
samples data are among the most important information
required by research scientists, reservoir engineers, and
geoscientists for reservoir characterization and description.
The following section presents two systems that were
developed aiming at analyzing the hydrocarbon phase
behavior and petrophysical data through an integrated
dynamic surveillance tool.
Hydrocarbon Phase Behavior Analysis System
This system was developed using the integrated dynamic
surveillance tool as a front-end, enabling the R&D scientists to
retrieve, report, visualize, map, and analyze pressure-volume-
temperature (PVT) properties data with ease. It provides the
user with an online access to several PVT properties data of
black oil and gas condensate fluids. Among the black oil data
are the PVT sample, hydrocarbon analysis, differential
liberation process, thermal expansion, compressibility,
bubblepoint, and volume-density-viscosity data. The gas
condensate data include depletion process analysis, retrograde
condensation, fluid composition, dewpoint, and pressure-
volume relations. The system can also be utilized by reservoir
simulation engineers in building and preparing the PVT input
data for the simulation models, and by reservoir management
engineers in conducting PVT-dependent field studies. The
system has resulted in significant savings of time and effort of
R&D scientists and engineers in conducting quality control,
experimental optimization, and research field studies.
Petrophysical Data Analysis Tool
Customized templates were also developed to help research
scientists retrieve petrophysical data from the corporate
database and display them for analysis and interpretation.
These petrophysical data include core porosity, permeability,
fluid saturation, hydraulic flow unit, reservoir quality index
(RQI), normalized porosity index (NPI), and flow zonation
indicator (FZI). Petrophysical data are extensively used in
interpretation, calculation, and completion of other technical
and research studies to support the development of oil and gas
reservoirs.
The main advantages of linking the petrophysical data to
the integrated surveillance tool through the corporate database
are:
Reducing the time required for retrieving core plug data
and allowing the engineer and scientist to use additional
derived functions to manipulate data or adding more
properties to core plugs, and
4 SPE 99555
Integration with complementary well data, such as
production and well test data, that may be used for better
interpretation and correlation of reservoir parameters.
Figures 11 to 13, show examples of analysis plots of
petrophysical data used by R&D scientists in conducting
research studies. The hydraulic unit is a statistical
representation of the reservoir zonation and reservoir quality.
The functions of the RQI and NPI are to quantify the flow
character of the reservoir and provide an association between
petrophysical properties and the micro and macro level
properties of the tested core samples. The FZI is commonly
used in conjunction with cluster analysis or probability plots to
differentiate between the flow zones.6
Well Test Knowledge Management System
A knowledge management system was developed to provide
well test analysis information in one environment. Figure 14
shows a schematic diagram of the well test knowledge
management system. The system is designed to display
pressure derivative signatures as thumb nails at the well
locations on a base map of any chosen field. A mouse-click on
each thumbnail enlarges it for detailed viewing and
interpretation. The system also allows the engineer to launch
the well test analysis application directly, for further analysis
and interpretation of any well test. This will help reduce the
time it takes to analyze a well test, by looking for patterns in
interpretation and comparing analysis results from nearby
wells.
Conclusion
In this paper, we have presented several software tools aimed
at automating the daily workflow processes of reservoir and
production engineers, as well as research scientists. These
automated tools proved to increase user productivity, reduce
time and effort, optimize operational activities, enhance
reservoir analysis, increase collaborative efforts between
reservoir and production engineers, and minimize human
errors, leading to improved efficiency of field management
practices. The integrated solutions are also dynamic, fully
automated, and capable of providing true performance
monitoring, with reliable real-time production and injection
data validation. Through these integrated dynamic tools,
engineers can efficiently manage oil and gas fields throughout
the E&P lifecycle, make better and quicker decisions based on
up-to-date production data, manage more wells in less time,
and detect production problems early in the well’s life.
Nomenclature
h =
formation thickness, ft.
k = permeability, md
q = oil rate, bbl/d
p = pressure drop, psi
re = outer reservoir radius, ft.
rw = wellbore radius, ft.
s = skin, dimensionless
Acknowledgement
We would like to thank Saudi Aramco management for their
permission to publish this paper.
Reference
1. Chan, K.S.: “Water Control Diagnostic Plots,” paper SPE 30775
presented at the 1995 SPE Annual Technical Conference and
Exhibition, Dallas, TX, October 22-25.
2. Reese, R.D.: “Completion Ranking Using Production
Heterogeneity Indexing,” paper SPE 36604 presented at the 1996
SPE Annual Technical Conference and Exhibition, Denver,
Colorado, October 6-9.
3. “Reservoir Optimization Workshop,” Schlumberger-DCS,
Houston, TX, June 2004.
4. Hall, H.N.: “How to Analyze Waterflood Injection Well
Performance,” World Oil (Oct. 1963) 128-130.
5. Earlougher, R.C.: Advances in Well Test Analysis. SPE
Monograph Series, Vol. 5, 1977.
6. “Special Core Analysis Study,” Report L-3309, Saudi Aramco,
June 2002.
SPE 99555 5
1969 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 2000 01 02 03 04 05 06 07 08 09 10 11 12 13 14
0
5000
10000
15000
20000
25000
Date
12
1. 103 : CASI NG LEAK REPAI R (PROD/ OBS) / COMPLETE/RE-COMPL I N SAME RS
2. 103 : FISHING/REMOVING OBSTRUCTION / COMPLETE/RE-COMPL IN SAME RSV
Oil Ra te, BCD
STIM
Rat e Fore cas t, BCD
WO
Wat er Ra te, BCD
Buildup
Falloff
Fig. 1- Remedial well analysis tool showing production history and forecast using decline curve analysis.
Fig. 2- Scatter plot of water cut and net pay thickness, with corresponding scatter plot of well locations.
6 SPE 99555
Fig. 3- Scatter plot of water cut and oil production rate, with corresponding scatter plot of well locations.
Fig. 4- Water diagnostic plots using water/oil ratio and water cut derivatives.
SPE 99555 7
Fig. 5- Scatter plots of heterogeneity index and well locations.
Fig. 6- A grid map of the formation damage index.
8 SPE 99555
Fig. 7- Integrated reservoir analysis tool.
Fig. 8- A typical example of Hall plot.
SPE 99555 9
Gas Plant
Pi server
Dynamic
Surveillance
Tool
Data in
Excel
Sheet
Excel
Sheet Excel
Sheet Excel
Sheet Excel
Sheet Excel
Sheet
Real Time
Production Data
Corporate
Database
Previous Data Flow New Data Flow
Gas Prod.
Engineering Gas Res.
Management
Gas Production Eng.
Prod. & Facilities
Development
Excel
sheets
Temporary
Database
Daily
Production
Database
End users
Corporate
Database
Gas Res. Management
Gas Plant
Pi server
Dynamic
Surveillance
Tool
Data in
Excel
Sheet
Excel
Sheet Excel
Sheet Excel
Sheet Excel
Sheet Excel
Sheet
Real Time
Production Data
Corporate
Database
Previous Data Flow New Data Flow
Gas Prod.
Engineering Gas Res.
Management
Gas Production Eng.
Prod. & Facilities
Development
Excel
sheets
Temporary
Database
Daily
Production
Database
End users
Corporate
Database
Gas Res. Management
Fig. 9- Past and current workflow processes of daily gas production data.
Real-Time
Production
Database
PI SCADA
Integrated Dynamic
Surveillance Tool
End Users
Plants
Real-Time
Production
Database
PI SCADA
Integrated Dynamic
Surveillance Tool
End Users
Plants
Fig. 10- Workflow of coupling integrated dynamic surveillance tool to Pi and SCADA systems.
Fig. 11- Flow zone indicator (FZI) correlated with adjusted core
and drilling depth. Fig. 12- Normalized porosity index (NPI) vs. reservoir quality index
(RQI).
Fig. 13- Permeability-porosity transform.
SPE 99555 11
Wells with well test interpretation
can be identified on the base map
Pressure derivative signatures can be compared with other wells
Additional well information can also be viewed
Well test package can be launched directly from within the
base map for additional interpretation
Wells with well test interpretation
can be identified on the base map
Pressure derivative signatures can be compared with other wells
Additional well information can also be viewed
Well test package can be launched directly from within the
base map for additional interpretation
Fig. 14- Well tests knowledge management system.
Article
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Reservoir Optimization Workshop
"Reservoir Optimization Workshop," Schlumberger-DCS, Houston, TX, June 2004.